Equbits presented at Lab Automation. Equbits was invited to present a podium presentation on the subject of interpretability of predictive models in a talk entitled "Myths and Realities about Interpretability in Predictive Modeling". This talk was part of the Informatics Track : Advances in Chemical Informatics Session, chaired by Peter Willet, Professor of Cheminformatics at University of Sheffield.

To learn more about the conference, please click here.

Equbits was selected as a best poster of the show and Hamilton Hitchings, Equbits Founder gave a podium presentation. The poster and presentation were on Local Modeling of ADME-Tox Properties demonstrating results for predicting mutagenicity of compounds. In addition, Dr. Gregory M. Banik, General Manager, Informatics Division, Bio-Rad Laboratories presented the power of Equbits Foresight for building local models using in-house data and generating consensus models with pre-built global models within Bio-Rad's KnowItAll® ADME Edition.

Drug Discovery and Technology
8th - 11th August, 2004 - Boston - MA
Link: http://www.drugdisc.com/section.htm?page=posters
Equbits exhibited a poster titled "A Comparative Estimation of Machine Learning Methods on QSAR Datasets" in the Lead Finding and Hits to Leads poster section. This poster showed superior results for modeling the NCI HIV HTS data set. In addition, Equbits demo'd their product in the Bio-Rad booth along with the tight integration with Bio-Rad's KnowItAll platform.

3rd Joint Sheffield Conference on Chemoinformatics
21st-23rd April, 2004 - Sheffield, UK
Link: http://cisrg.shef.ac.uk/shef2004/
Equbits exhibited a poster titled "A Comparison of Machine Learning Methods on HTS and ADME-Tox Data".

American Chemical Society
227th ACS National Meeting • March 28 - April 1, 2004 • Anaheim, California
Link: http://www.chemistry.org/portal/a/c/s/1/acsdisplay.html?DOC=meetings%5canaheim2004%5cindex.html

Statistical Learning and Data Mining Short Course
Sheraton Palo Alto, California: February 26 - 27, 2004
Link http://www-stat.stanford.edu/~hastie/mrc.html
A two-day course independently offered and taught by Stanford University Professor (and Equbits Advisor) Trevor Hastie and his Stanford colleague Rob Tibshirani. Covering material from Supervised to Unsupervised Learning, widely applicable statistical methods for data analysis.

Equbits Presented at CHI Predictive ADME & Toxicology 2003
Boston, MA, November 19th, 2003 - Equbits presented at CHI Predictive ADME and Toxicology on Wednesday, November 19th. A premiere conference for the drug discovery arena, the CHI conference covered discussions around predictive modeling in the areas of ADME-Tox. As a part of the conference, Equbits presented results using Equbits Foresight™ on a number of known data sets, comparing commonly used methodologies/algorithms/products to results generated by Equbits Foresight's novel patent pending technology.

Take the opportunity to learn more about our core technology, how we differ from existing methodologies, and how you can become an evaluator of our exciting new software.